In conventional motor vehicles (e.g., automobiles, cars, trucks, buses, etc.), the driver is critical to operating the vehicle's control system. For example, the driver of a conventional motor vehicle makes decisions regarding the safe operation of the vehicle. Such decisions may include decisions related to the speed of the vehicle, steering of the vehicle, obstacle and/or hazard recognition, and obstacle and/or hazard avoidance. However, a driver's ability to make these decisions and operate the vehicle's control system may be limited in some situations. For example, driver impairment, fatigue, attentiveness, and/or other factors such as visibility (e.g., due to weather or changes in terrain) may limit a driver's ability to safely operate a conventional motor vehicle and/or its control system.
In order to alleviate the deficiencies resulting from driver operation of a conventional motor vehicle, various manufacturers have experimented with autonomous vehicles. While autonomous vehicles may allow for a reduction in issues that may arise as a result of the driver's ability to operate the conventional motor vehicle becoming lessened, autonomous vehicles have their own shortcomings.
For example, autonomous vehicles may rely on artificial intelligence and/or machine learning. Artificial intelligence and machine learning require large amounts of memory bandwidth, which can be difficult to achieve given the constraints of I/O technology, power, and packaging. For example, concerning power, thermal management and battery life must be considered. With regards to safety, system components in autonomous vehicles need to be reliable because failure of one or more system components could result in injury or death to passengers in the autonomous vehicle. To decrease the chance of system failure, system components can be reduced, however a lower component count is generally in conflict with meeting performance requirements of a system.